Steg.ai - OpenText Product Traceability Integration and Automation

Common Integration Use Cases Between Steg.ai and OpenText Product Traceability

1. Automated product image tagging for traceability records

Data flow: Steg.ai - OpenText Product Traceability

Steg.ai can analyze product images, packaging photos, and label assets to extract visual attributes such as product type, variant, packaging format, and compliance markings. These tags can be pushed into OpenText Product Traceability to enrich traceability records with image-based metadata. This helps operations, quality, and supply chain teams quickly identify products and packaging versions during audits, recalls, or investigations.

2. Packaging artwork validation against traceability master data

Data flow: OpenText Product Traceability - Steg.ai

OpenText Product Traceability can provide approved product identifiers, lot details, and packaging specifications to Steg.ai for image comparison and classification. Steg.ai can then validate whether packaging artwork, labels, and carton images match the expected traceability data. This reduces labeling errors, supports pre-production checks, and helps prevent non-compliant packaging from reaching the market.

3. Content protection for regulated product documentation

Data flow: Steg.ai - OpenText Product Traceability

Steg.ai can apply content protection and asset intelligence to sensitive product images, certificates, and traceability documents before they are stored or shared through OpenText Product Traceability. This is valuable for regulated industries where product specifications, batch records, and serialized asset images must be protected from unauthorized use. It improves governance while maintaining controlled access to critical traceability evidence.

4. Visual evidence capture for quality and recall workflows

Data flow: Bi-directional

When a quality issue or recall event is logged in OpenText Product Traceability, related images from production, warehouse, or field inspections can be sent to Steg.ai for classification and tagging. Steg.ai can return enriched metadata such as defect type, packaging condition, or product variant, which is then stored back in OpenText Product Traceability. This creates a faster, more searchable evidence trail for root cause analysis and recall coordination.

5. Automated classification of serialized assets and packaging variants

Data flow: Steg.ai - OpenText Product Traceability

Steg.ai can classify images of serialized products, cartons, and pallets to identify packaging variants, label formats, and visual differences across production runs. OpenText Product Traceability can use this information to link visual assets to specific serial numbers, batches, or lots. This supports warehouse verification, shipment validation, and downstream traceability across complex product hierarchies.

6. Supplier-submitted image intake and validation

Data flow: OpenText Product Traceability - Steg.ai

Suppliers can submit product photos, label proofs, or packaging samples through OpenText Product Traceability, which then forwards the assets to Steg.ai for automated recognition and tagging. The results can confirm whether supplier materials align with approved product specifications and traceability requirements. This streamlines supplier onboarding, packaging approval, and incoming quality checks.

7. Audit-ready traceability dossiers with enriched visual metadata

Data flow: Steg.ai - OpenText Product Traceability

Steg.ai can enrich stored product images and documents with searchable tags such as product family, region, packaging type, and compliance indicators. OpenText Product Traceability can then assemble these assets into audit-ready dossiers for regulators, internal auditors, or customer inquiries. This reduces manual document preparation and improves the speed and accuracy of compliance reporting.

8. Cross-team workflow for product change management

Data flow: Bi-directional

When a product change is initiated in OpenText Product Traceability, updated packaging references and product specifications can be sent to Steg.ai for image reclassification and comparison against existing assets. Steg.ai can flag outdated artwork, mismatched labels, or obsolete packaging images and return the results to traceability teams. This supports coordinated work across regulatory, quality, packaging, and supply chain teams, reducing the risk of using outdated product materials.